Field of the Invention
The present invention relates to an image processing apparatus and an image processing method in a tomographic image diagnosis using X-rays.
Description of the Related Art
Although it has been more than 40 years since a diagnosis apparatus based on a tomographic image using X-rays was commercialized in the 1970s, the diagnosis apparatus is still developing and stays in action, taking a leading role in a diagnosis technique. Recently, due to the speeding up of processing and the increase in memory amount brought about by the advancement of computer hardware, products using iterative reconstruction (sequential approximation reconstruction), which have been traditionally considered difficult to commercialize, have become commercially available.
Unlike filtered back projection, iterative reconstruction is a method that uses algebraic reconstruction. In this method, the tomographic image is obtained sequentially by repeating forward projection and back projection so that a projection image of the tomographic image matches a projection image which is actually imaged.
Iterative reconstruction spends much more time on reconstruction than filtered back projection. However, because it is possible to incorporate various mathematical models into reconstruction, scattered ray correction, artifact correction, detector resolution correction, noise reduction, and the like can be considered. This enables generation of a tomographic image with a higher signal-to-noise (S/N) ratio than was previously possible and suppression of artifacts.
Regulation is one of the most important elements in mathematical models. Regulation is a means for providing a priori information of a tomographic image as a constraint condition in reconstruction. For example, Thikonov-Philips regulation, which provides continuity of pixel values of a tomographic image as a constraint condition, is famous. In addition, L1 norm regulation used in the field of inverse problems such as Compressed Sensing has been applied to reconstruction in recent years.
A reconstruction method of changing the degree of regulation depending on a pixel value difference (contrast) of the tomographic image is described in U.S. Pat. No. 8,005,286 (“literature 1”, hereinafter) and “A three-dimensional statistical approach to improved image quality for multislice helical CT”, Thibault, J. B. et al., Med. Phys., vol. 34, issue 11 (2007) (“literature 2”, hereinafter). These approaches weaken the degree of regulation in an area of a large pixel value difference, and strengthen the degree of regulation in an area of a small pixel value difference.
Generally, the noise amount differs depending on the pixel value in an X-ray image. Furthermore, in the tomographic image, the noise amount is never the same even when the pixel value (CT value) is the same. This is because the tomographic image is reconstructed from a plurality of projection images, and the noise amount cannot be decided.